Enhanced Multilinear PCA for Efficient Image Analysis and Dimensionality Reduction: Unlocking the Potential of Complex Image Data by Tianyu Sun, Lang He, Xi Fang, Liang Xie

“…The proposed EMPCA algorithm holds promise for reducing image analysis runtimes and advancing rapid image processing techniques.…”
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Fault Diagnosis of Hydraulic Pumps Using PSO-VMD and Refined Composite Multiscale Fluctuation Dispersion Entropy by Fuming Zhou, Xiaoqiang Yang, Jinxing Shen, Wuqiang Liu

“…Finally, particle swarm optimization support vector machine (PSO-SVM) is adopted to distinguish different work states of hydraulic pumps. …”
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A Real-Time Key-Finding Algorithm Based on the Signature of Fifths by Paulina KANIA, Dariusz KANIA, Tomasz ŁUKASZEWICZ

“…The technique is based on geometrical relationships existing between twelve polar vectors inscribed in the circle of fifths, which represent individual pitch-classes detected in a given composition. …”
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Water‐to‐Air Imaging: A Recovery Method for the Instantaneous Distorted Image Based on Structured Light and Local Approximate Registration by Bijian Jian, Ting Peng, Xuebo Zhang, Changyong Lin

“…Then, the displacement information of the feature points on the distorted structured light image and the standard structured light image is obtained through the feature extraction algorithm and is used to estimate the distortion vector field of the corresponding sampling points in the distorted scene image. …”
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Interval Forecasting of Carbon Futures Prices Using a Novel Hybrid Approach with Exogenous Variables by Lu Zhang, Junbiao Zhang, Tao Xiong, Chiao Su

“…Specifically, the purpose of this study is to present a novel hybrid approach, which is composed of multioutput support vector regression (MSVR) and particle swarm optimization (PSO), in the task of forecasting the highest and lowest prices of carbon futures on the next trading day. …”
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A Feature-Selective Independent Component Analysis Method for Functional MRI by Yi-Ou Li, Tülay Adali, Vince D. Calhoun

“…The feature-selective scheme is achieved through a filtering operation in the source sample space followed by a projection onto the demixing vector space by a least squares projection in an iterative ICA process. …”
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Detection of Wood Boring Insects’ Larvae Based on the Acoustic Signal Analysis and the Artificial Intelligence Algorithm by Piotr BILSKI, Piotr BOBIŃSKI, Adam KRAJEWSKI, Piotr WITOMSKI

“…The paper presents an application of signal processing and computational intelligence methods to detect presence of the wood boring insects larvae in the wooden constructions (such as the furniture of buildings). …”
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Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

“…In this paper, we propose an optimized combined forecasting model by ant colony optimization algorithm (ACO) based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and support vector machine (SVM) to improve the forecasting accuracy. …”
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Application of KTA-KELM in Fault Diagnosis of Rolling Bearing by Zhuo Wang, Wenjun Zhao, Tao Ma, Zhijun Li, Bo Qin

“…Finally，the high-dimensional feature vector set of the above rolling bearing is used as input to learn the KTA-KELM algorithm, the state recognition model of rolling bearing is built based on KTA-KELM algorithm. …”
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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

“…The performance of the models and data quality improved when emphasizing the impact of feature selection and data pre-processing approaches. Five machine learning models were evaluated by utilizing the Edge-IIoTset dataset: Random Forest (RF), Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and K-Nearest Neighbors (KNN) with multiple K values, and Convolutional Neural Network (CNN). …”
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Predicting Intensive Care Unit Admissions in COVID-19 Patients: An AI-Powered Machine Learning Model by A. M. Mutawa

“…We employed various ML classifiers, including support vector machines (SVM). The SVM model surpasses all other models in terms of precision (0.99) and area under curve (AUC, 0.91). …”
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Transient Stability Assessment Model With Sample Selection Method Based on Spatial Distribution by Yongbin Li, Yiting Wang, Jian Li, Huanbei Zhao, Huaiyuan Wang, Litao Hu

“…Sample selection aims to optimize the training set to speed up the training process while improving the preference of the TSA model. …”
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Designing an intelligent push model for user emotional topics based on dynamic text categorization in social media news dissemination by Jixuan Wang

“…The model initiates data input processing by employing word segmentation and word vector extraction, culminating in the formation of an attention-based bidirectional long short-term memory (ATT-Bi-LSTM) model, which incorporates an attention mechanism for discerning positive and negative emotions. …”
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‘Only Brooks of Sheffield’: Conversation, Crossover Writing, and Child and Adult Perspectives in David Copperfield and Its Juvenile Adaptations by Hannah Field

“…First, I show conversation as an important vector in Dickens’s exploration of child and adult knowledge in the original novel. …”
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Classifying software security requirements into confidentiality, integrity, and availability using machine learning approaches by Taghreed Bagies

“…For both techniques, we developed five models by using five well-known machine learning algorithms: (1) support vector machine (SVM), (2) K-nearest neighbors (KNN), (3) Random Forest (RF), (4) gradient boosting (GB), and (5) Bernoulli Naive Bayes (BNB). …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Then, by introducing the decision tree algorithm, the overfitting is reduced and the data processing speed of the model is improved, and on this basis, the feature selection is carried out through the “gain rate” optimization method, which reduces the redundant information of the feature vector. …”
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Development of AI-Based Public Safety System with Face Recognition Using CNN and SVM Models in Real-Time by Naila Ratu Alifa, Yana Cahyana, Rahmat Rahmat, Sutan Faisal

“…This study aims to develop an Artificial Intelligence (AI)-based system using Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for gender identification in order to support sexual crime investigations. …”
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Evaluating Grayware Characteristics and Risks by Zhongqiang Chen, Zhanyan Liang, Yuan Zhang, Zhongrong Chen

“…A grayware categorization framework is therefore proposed here to not only classify grayware according to diverse taxonomic features but also facilitate evaluations on grayware risk to cyberspace. Armed with Support Vector Machines, the framework builds learning models based on training data extracted automatically from grayware encyclopedias and visualizes categorization results with Self-Organizing Maps. …”
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Quantum resonant dimensionality reduction by Fan Yang, Furong Wang, Xusheng Xu, Pan Gao, Tao Xin, ShiJie Wei, Guilu Long

“…The simulation results indicate that reduced data extremely improved the processing efficiency following the application of QRDR. …”
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STUDY ON MECHANICAL PROPERTIES OF SPATIAL INTERSECTION CONCAVE HONEYCOMB STRUCTURE

“…As a typical negative Poisson's ratio structure,the concave hexagon is commonly used in modern energy absorption devices.Based on the honeycomb structure and the concave hexagon,five kinds of structures were firstly obtained through space intersection design.The deformation mechanism and structural mechanical characteristics of five kinds of structures were discussed by finite element simulation and compression test.Then,the transient equivalent calculation method of structural counter-force was given by using vector analysis method,and the calculation formulas of counter-force,collision velocity and acceleration were derived.Counter-force calculation results were compared with compression test,and the test results were basically consistent with the theoretical results.Finally,the optimal structure was filled into the crash box,and the collision simulation analysis was processed with the new crash box.It is found that the mechanical properties of concave honeycomb stucture(CHS)cells with negative Poisson's ratio are better than those of the traditional honeycomb structure(THS).In the second type of structure,C-C structure can increase the structural deformation and reduce the stress.And the stress distribution of C-C structure is more uniform than that of the other structure.The collision simulation results show that the C-C structure crash box can greatly reduce the peak values of speed and acceleration,and the acceleration value is far less than the 40g,which reaches standard in the vehicle collision specification.At the same time,compared with the traditional crash box structure,the energy absorption of the new designed sandwich structure crash box is improved by more than 3 times.…”
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